A presentation introducing image processing and artificial intelligence

2. An introduction to
IMAGE PROCESSING &
ARTIFICIAL INTELLIGENCE

3. What is an Image?
In literature terms: Image is a word or phrase
that directs to taste, sound, hear, sight, smell
In general term: Image is a picture expressing
ones self
In computer science
an image is an exact
replica of the contents of a storage device stored on
a second storage device

6. What is Image Processing?
Analyzing and manipulating images with a computer. Image
processing generally involves three steps:
1. Import an image with an optical scanner or directly through
digital photography.
2. Manipulate or analyze the image in some way. This stage can
include image, enhancement and data compression, or the image may
be analyzed to find patterns that aren't visible by the human eye. For
example, meteorologists use image processing to analyze satellite
photographs.
3. Output the result The result might be the image altered in some
way or it might be a report based on analysis of the image.

7. What is Noise?
Image noise is the random variation of brightness or
color information in images produced by the sensor and
circuitry of a scanner or digital camera.

8. How to Remove Noise from Images
An edge-sensitive noise reduction algorithm for digital
image processing is proposed. It is designed as C-DLL to
run as a macro command under Image-Pro Plus. Its
properties are compared to the median filter and a simple
smoothing kernel.

10. Color Enhancement
Methods of electronically enhancing one or
more color components (C, Y, M) which
together
represent
the
chromatic
components of a pixel of an image.

13. Color
Enhancement

14. Sharpening In Image
Sharpening is an image-manipulation technique for making
the outlines of a digital image look more distinct. Sharpening
increases the contrast between edge pixels and emphasizes
the transition between dark and light areas. Sharpening
increases local contrast and brings out fine detail. There is no
strict formula for correctly sharpening all images. Too little
sharpening can make for a soft image, but over-sharpening
adds noise.
Methods of Sharpening the Image
Gradient Operator
Laplacian operator

15. Sharpening

16. Segmentation

17. Segmentation

18. Segmentation

19. Edge Detection
Egg
Detection

20. Feature Detection & Recognition

23. Representation Issues

24. Questions & Answers

25. References
http://www.dl-c.com/sharpen.pdf
http://www.lsv.uni-saarland.de/dsp_ss05_chap8.pdf
http://www.societyofrobots.com/programming_computer_
vision_tutorial_pt3.shtml
http://smartbanksecurity.com/design.html
http://www.pages.drexel.edu/~weg22/edge.html